README.md

---
license: apache-2.0
library_name: lerobot
tags:
  - robotics
  - imitation-learning
  - aloha
  - act
  - lerobot
datasets:
  - lerobot/aloha_sim_insertion_human_image
pipeline_tag: robotics
---

# ACT Model for ALOHA Insertion Task

A lightweight Action Chunking with Transformers (ACT) model trained on the ALOHA simulation Insertion task. This is a **difficult bimanual coordination task** with lower success rate compared to TransferCube.

## Model Description

| Property | Value |
|----------|-------|
| Architecture | ACT (Action Chunking with Transformers) |
| Parameters | 52M |
| Task | ALOHA Insertion-v0 |
| Training Steps | 200,000 |
| Batch Size | 32 |
| Success Rate | ~15% |

## Training Data

- **Dataset**: [lerobot/aloha_sim_insertion_human_image](https://huggingface.co/datasets/lerobot/aloha_sim_insertion_human_image)
- **Episodes**: 50 human demonstrations
- **Frames**: 20,000

## Task Description

The Insertion task requires a bimanual robot to:
1. Pick up a socket with the left arm
2. Pick up a peg with the right arm
3. Insert the peg into the socket in mid-air

⚠️ **This is a difficult task** requiring precise bimanual coordination. Success rate is significantly lower than TransferCube.

## Demo Video

<video controls src="eval_episode_3.mp4" title="Insertion Demo"></video>

## Training Environment

- **GPU**: RTX A6000
- **Framework**: LeRobot 0.4.3
- **Training Time**: Around 13 hours

## Usage

### Installation
```bash
pip install lerobot gym-aloha
```

### Training
```bash
lerobot-train \
    --policy.type=act \
    --dataset.repo_id=lerobot/aloha_sim_insertion_human_image \
    --env.type=aloha \
    --env.task=AlohaInsertion-v0 \
    --batch_size=32 \
    --steps=200000 \
    --eval.n_episodes=10 \
    --eval_freq=20000 \
    --save_freq=20000 \
    --output_dir=./outputs/act_aloha_insertion \
    --wandb.enable=false \
    --policy.push_to_hub=false
```

### Evaluation
```bash
lerobot-eval \
    --policy.path=LeTau/act_aloha_insertion \
    --env.type=aloha \
    --env.task=AlohaInsertion-v0 \
    --eval.batch_size=1 \
    --eval.n_episodes=20
```

### Fine-tuning
```bash
lerobot-train \
    --resume=true \
    --config_path=LeTau/act_aloha_insertion/train_config.json \
    --steps=300000
```

## Results

| Evaluation | Episodes | Success Rate | Avg Sum Reward |
|------------|----------|--------------|----------------|
| Training (120K) | 10 | 10% | 40.3 |
| Training (200K) | 10 | 20% | 40.4 |
| Independent | 20 | 15% | 51.2 |

**Expected success rate: 15-20%**

### Task Difficulty Comparison

| Task | Difficulty | Success Rate |
|------|------------|--------------|
| TransferCube | Easy | 35-42% |
| **Insertion** | **Hard** | **15-20%** |

## Detailed Evaluation Results (Independent)
```
Sum Rewards: [0.0, 0.0, 0.0, 240.0, 121.0, 0.0, 0.0, 0.0, 43.0, 0.0,
              256.0, 0.0, 0.0, 321.0, 0.0, 0.0, 0.0, 0.0, 43.0, 0.0]

Successes: 3/20 episodes
```

## Limitations

- **Difficult task**: Insertion requires precise bimanual coordination
- **Limited training data**: Only 50 demonstration episodes available
- **Low success rate**: This is a baseline model for a challenging task
- **Single task**: Only trained on Insertion, no multi-task capability


## Citation
```bibtex
@article{zhao2023learning,
  title={Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware},
  author={Zhao, Tony Z and Kumar, Vikash and Levine, Sergey and Finn, Chelsea},
  journal={arXiv preprint arXiv:2304.13705},
  year={2023}
}
```

## Acknowledgments

- [LeRobot](https://github.com/huggingface/lerobot) framework by HuggingFace
- [ALOHA](https://tonyzhaozh.github.io/aloha/) project by Stanford